Saju SR, Sr Vice President, Smart Power Division, Electrification Business, ABB India.

What are the new technologies in automation that will be game-changers for factories in 2025?

Key technologies propelling digital transformation in industries today include generative artificial intelligence (Gen AI), data analytics, machine learning (ML), and the combination of cloud and edge computing. These advanced tools play a pivotal role in optimising operational efficiency, improving process performance, and driving sustainability initiatives.

Foundational solutions such as advanced process control (APC), energy management systems (EMS), and manufacturing execution systems (MES) continue to form the backbone of industrial processes. However, their functionality is increasingly being expanded through innovative applications tailored to meet the unique demands of various sectors.

ABB India is at the forefront of enabling this digital shift by supporting the seamless integration of real-time data transmission capabilities and implementing robust cybersecurity frameworks. These measures ensure that digital operations remain secure, resilient, and efficient. Powered by ABB Ability™, the company’s unified, cross-industry digital platform and its deep industry expertise, ABB is helping companies to increase productivity, enhance operational efficiency, and improve safety and security.

Furthermore, collaborative efforts through partnerships and co-creation initiatives are accelerating the adoption and scalability of transformative technologies. By leveraging these advanced digital tools, industries are not only advancing toward net-zero emissions but also achieving unparalleled levels of productivity and operational excellence.

With the growth of Industrial IoT, how do you foresee trends like connected workspaces, AI/ML, robotics and the industrial metaverse influencing factory operations?

Artificial intelligence is revolutionising automation by driving new levels of autonomy, expanding applications across diverse industries, and making advanced technologies more accessible to a wider range of users. AI advancements enable machines to perform complex tasks such as precise object manipulation, decision-making, and navigating dynamic environments with greater efficiency. For example, technologies like Visual Simultaneous Localisation and Mapping (Visual SLAM) empower systems to autonomously map and adapt to their surroundings, reducing the need for extensive infrastructure and enabling more flexible operations.

AI-powered automation is also transforming human-machine collaboration. Intuitive AI interfaces, including generative AI, allow users to interact with systems through natural language, making it easier for individuals without technical expertise to engage with these technologies. This lowers entry barriers, allowing a broader workforce to leverage automation, especially beneficial for small and medium-sized enterprises addressing labour shortages.

Additionally, AI’s predictive capabilities enhance operational efficiency by supporting predictive maintenance, which is vital in industries like automotive manufacturing, where downtime can be expensive. Machine learning algorithms analyse data from similar automated processes to continuously optimise performance, driving higher productivity and reducing inefficiencies.

What challenges do factories face in integrating legacy systems with new automation technologies?

Integrating legacy systems with new automation technologies poses several challenges to factories. One of the primary issues is the existence of outdated IT infrastructure that is incompatible with modern software. This incompatibility hinders the organisation's ability to effectively analyse production, sensor, and other critical data, thereby limiting its operational efficiency and productivity.

Another significant challenge is the high cost and complexity of retrofitting. Upgrading old systems to make them compatible with new technologies can be expensive and time-consuming, and in many cases, may not be feasible due to the age and limitations of the existing equipment.

Furthermore, as more shop floor machines are connected to the internet to facilitate automation, cybersecurity becomes a major concern. The increased connectivity can expose the organisation to various data security threats, putting sensitive information at risk.

Lastly, many factories have machines that have been in operation for decades, which often have limited or no sensor and internet connectivity. This makes it difficult, if not impossible, to integrate them with IIoT devices, further complicating the transition to automated systems.

How are sustainability goals influencing automation strategies in manufacturing?

Sustainability and environmental considerations are reshaping automation strategies, driving the adoption of advanced industrial software solutions designed to enhance transparency and optimise resource utilisation. These technologies provide an integrated platform to monitor key metrics such as emissions, energy consumption, and regulatory compliance. By enabling data-driven decision-making, they help industries minimise environmental impact and achieve sustainability targets.

Through process optimisation and predictive maintenance, industrial software significantly reduces energy usage, emissions, and waste, aligning with broader environmental goals. As organisations work to lower their carbon footprint, digital transformation strategies are increasingly centered around efficiency, resource conservation, and the adoption of circular economy principles to meet sustainability objectives while improving operational performance.

(The views expressed in interviews are personal, not necessarily of the organisations represented) 

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